Using a combination of pharmacology, electrophysiology, and simple modeling, we have investigated the role of local GABAA inhibition in shaping the output of neurons in cat primary visual cortex. We have recorded from cells before, during and after iontophoresis of the highly selective GABAA antagonist gabazine. The results indicate that GABAA inhibition contributes in simple ways to the sensitivity and selectivity of V1 neurons.
Our first set of results concerns the sensitivity of neurons: we found that local GABAA
inhibition controls the response gain but not the contrast gain of V1 neurons. These results contradict earlier proposals for a key role of GABAA
inhibition in contrast gain control (Carandini and Heeger, 1994
; Carandini et al., 1997
; Somers et al., 1998
), as they indicate that the contrast sensitivity of V1 neurons does not rely on intracortical inhibition. This conclusion may well extend to other cortical areas; for instance, contrast sensitivity in area MT of primates is unaffected by blocking inhibition with bicuculline (Thiele et al., 2004
These results suggest that GABAA
inhibition may be a natural substrate for the control of responsiveness seen during the deployment of visual attention. A recent study, indeed, argues that attention changes the response gain but not the contrast gain of V1 neurons (Lee and Maunsell, 2010
). Attention could achieve this goal rather simply if it acted on the strength of GABAA
Our finding that cross-orientation suppression is unaffected by gabazine is direct evidence that this form of suppression does not rely on intracortical inhibition. This finding corroborates the interpretation of previous studies that provided indirect evidence against a role of inhibition in cross-orientation suppression (Carandini et al., 2002
; Freeman et al., 2002
; Li et al., 2006
; Priebe and Ferster, 2006
). In fact, the only data supporting a GABAergic origin of cross-orientation suppression were obtained by blocking inhibition with a diffuse application of bicuculline (Morrone et al., 1987
). The interpretation of those data is made difficult by the limitations of bicuculline (Debarbieux et al., 1998
Contrast saturation and cross-orientation suppression are key pieces of evidence for divisive normalization in V1 (Busse et al., 2009
; Carandini et al., 1997
; Heeger, 1992
). Our results show that they don't rely on GABAA
inhibition, and thereby falsify an early proposal for the biophysical substrate of normalization (Carandini and Heeger, 1994
; Carandini et al., 1997
). Normalization is now thought to rely on alternative mechanisms, at least for phenomena that arise within the receptive field (Carandini et al., 2002
; Finn et al., 2007
; Priebe and Ferster, 2006
). It is currently unclear whether normalization relies on GABAA
inhibition for suppression originating in the surrounding regions (Haider et al., 2010
; Ozeki et al., 2009
Our second set of results concerns stimulus selectivity: we found that local GABAA inhibition contributes to the selectivity of V1 neurons for stimulus orientation and direction. Inhibition contributes to selectivity simply by matching the selectivity of excitation, thereby keeping the responses to most stimuli below threshold.
The effects of gabazine on tuning curves – increased firing rates, broadened tuning width, and reduced direction selectivity – confirm some but not all of the previous results obtained with bicuculline. Earlier studies reported very strong effects: bicuculline was seen to broaden markedly the selectivity for orientation or direction of most neurons, in some cells abolishing it altogether (Eysel and Shevelev, 1994
; Pettigrew and Daniels, 1973
; Rose and Blakemore, 1974
; Sillito, 1975
; Sillito, 1979
; Sillito et al., 1980
; Tsumoto et al., 1979
). More recent studies, however, reported subtler effects that are more similar to the ones we observed (Li et al., 2008
; Ozeki et al., 2004
; Sato et al., 1996
). As with gabazine, the size of the effects seen with bicuculline depended on the degree to which neurons are selective in the first place (Li et al., 2008
). Overall, the large variability of effects reported in bicuculline studies might be related to the inferior selectivity and non-GABAergic side effects of this drug (Debarbieux et al., 1998
; Kurt et al., 2006
; Wermuth and Bizière, 1986
), or to differences in doses across studies.
To capture the effects of gabazine on orientation tuning curves we considered a simple cellular model based on a precise match between the tuning of inhibition and excitation. Excitation and inhibition in visual cortex have similar selectivity for orientation (Anderson et al., 2000
; Marino et al., 2005
; Monier et al., 2003
) though perhaps not for direction (Monier et al., 2003
; Priebe and Ferster, 2005
) or for stimulus size (Haider et al., 2010
; Ozeki et al., 2009
). The selectivity of inhibition matches that of excitation also in somatosensory cortex (Okun and Lampl, 2008
) and in auditory cortex (Wehr and Zador, 2003
). Inhibition and excitation, moreover, are matched not only in sensory-evoked activity, but also in the ongoing activity (Adesnik and Scanziani, 2010
; Haider et al., 2006
; Okun and Lampl, 2008
). This match between excitation and inhibition, therefore, may be a fundamental organizing principle of neocortex (but not necessarily all of cortex, see Poo and Isaacson, 2009
The cellular model that we considered incorporates highly simplified assumptions. First, it assumes that membrane potential is the result of the subtraction of inhibition from excitation. Subtraction is a simplification because inhibition does provide conductance increases at least at some orientations (Anderson et al., 2000
; Borg-Graham et al., 1998
), which would result in a non-linear integration of synaptic inputs (a fact that we did include in our simulations based on intracellular data). Second, the model assumes that the relationship between firing rate and the underlying membrane potential is simply a threshold followed by a linear dependence. Intracellular measurements support this notion, but also indicate that noise in the membrane potential (which we ignored) smoothes the threshold and turns it into an exponent (Carandini, 2004
; Carandini and Ferster, 2000
; Priebe and Ferster, 2008
). Third, we assumed that the responses observed under gabazine mostly reflect excitatory synaptic inputs, as synaptic inhibition has been largely abolished. This is oversimplified, as gabazine is likely to have reached the perisomatic region more than the distal dendrites (see below). Also, though GABAB
receptors are unlikely to shape transient visual responses, they may contribute to responses on the scale of seconds. Finally, we assumed that gabazine affected only inhibition, whereas it is likely to have increased (and slightly broadened in tuning) the excitation that the neurons receive from the local network.
Even though it was so highly simplified, the model provided a full account of the effects of gabazine on orientation tuning. It predicted the effects of gabazine on overall responsiveness, tuning width, and direction selectivity. This success suggests that all the effects of gabazine – including those that had earlier been ascribed to broadly tuned inhibition – can be explained by inhibition having the same tuning as excitation.
One limitation of our study is that it addresses mostly the inhibition that neurons receive near the soma. Our electrode likely recorded signals near the soma, and given that the ejecting pipette was 20 μm away, the concentration of gabazine is likely to have been largest in the perisomatic region. Concentration at the distal dendrites may have been low, given that gabazine did not affect electrode arrays implanted 0.5–1.5 mm away from the ejecting pipette.
The conclusions that can be drawn from this study, therefore, concern mostly perisomatic inhibition, rather than inhibition on distal dendrites. Indeed, this limitation that is shared with many other studies on the role of inhibition. Intracellular studies of the orientation tuning of excitation and inhibition, for instance, are largely based on currents injection at the soma. These currents do not fully spread to distal dendrites (Williams and Mitchell, 2008
), so the conductances that are estimated are largely perisomatic.
Another limitation of our study concerns the specificity of our manipulations. While we strived to keep the injection of gabazine local, the drug is likely to have spread beyond the neuron under study, potentially altering the function of local microcircuits. Substances applied iontophoretically with similar methods can diffuse as much as 200–600 μm (Candy et al., 1974
). Pyramidal neurons in sensory cortex excite one another over comparable distances (Thomson and Lamy, 2007
). Therefore, the increase in responsiveness seen with gabazine might be due not only to cellular effects – the blockade of perisomatic GABAA
receptors – but also to network effects: an increase in mutual excitation brought about by increased responsiveness in interconnected neurons. We can't distinguish these two effects, and neither can all previous studies that attempted to block inhibition, with the exception of one that blocked inhibition intracellularly (Nelson et al., 1994
). The good agreement between our results and those of that study indicates that the main effects that we observed are cellular.
In conclusion, we found that local inhibition mediated by GABAA receptors controls tuning width and direction selectivity not by being broadly tuned, but rather by working hand in hand with an excitatory drive that has the same selectivity. Together, excitation and inhibition exploit the ability of the spike threshold to sharpen orientation tuning, improve direction selectivity, and set the appropriate responsiveness. GABAA inhibition plays a substantial role in the control of responsiveness: it makes neurons more or less responsive to stimuli, without affecting their sensitivity to contrast. In other words, GABAA inhibition does not participate in input gain control, but rather is a determinant factor in response gain control.